Dear all,
We submitted the paper "Incremental Common Criteria Certification
Processes using DevSecOps Practices" to EuroSPW 2021. We request to
acknowledge SPARTA if the paper is accepted.
Abstract:
The growing digitalisation of our economies and societies is driving the
need for increased connectivity of critical applications and
infrastructures to the point where failures can lead to important
disruptions and consequences to our lives. One growing source of
failures for critical applications and infrastructures originates from
cybersecurity threats and vulnerabilities that can be exploited in
attacks. One approach to mitigating these risks is verifying that
critical applications and infrastructures are sufficiently protected by
certification of products and services. However, reaching sufficient
assurance levels for product certification may require detailed
evaluation of product properties. An important challenge for product
certification is dealing with product evolution: now that critical
applications and infrastructures are connected they are being updated on
a more frequent basis. To ensure continuity of certification, updates
must be analysed to verify the impact on certified cybersecurity
properties. Impacted properties need to be re-certified. This paper
proposes a lightweight and flexible incremental certification process
that can be integrated with DevSecOps practices to automate as much as
possible evidence gathering and certification activities. The approach
is illustrated on the Common Criteria product certification scheme and a
firewall update on an automotive case study. Only the impact analysis
phase of the incremental certification process is illustrated.
Best Regards,
--
Sebastien Dupont
Expert Research Engineer
Model-Based Engineering and Distributed Systems
CETIC
Avenue Jean Mermoz 28
B-6041 Charleroi
Tel: +32 488 237 483
Dear All,
I am pleased to inform that our new Open Acces paper is now published in
journal 'Scientific Reports' (IF=4,379):
Szczepański, M., Pawlicki, M., Kozik, R. et al. New explainability method
for BERT-based model in fake news detection. Sci Rep 11, 23705 (2021).
https://doi.org/10.1038/s41598-021-03100-6
Available at:
https://www.nature.com/articles/s41598-021-03100-6https://www.nature.com/articles/s41598-021-03100-6.pdf
It addresses explainability for fake detection based on machine learning
(in cooperation with project H2020 SocialTruth)
Kind Regards,
Prof. Michal Choras